Publication Details

Category Data Publication
DOI 10.5281/zenodo.6614860
Licence creative commons licence
Title (Primary) Dataset for the paper: Computational framework for radionuclide migration assessment in clay rocks [Data set]
Author Garibay-Rodriguez, J.; Chen, C. ORCID logo ; Shao, H. ORCID logo ; Bilke, L. ORCID logo ; Kolditz, O. ORCID logo ; Montoya, V.; Lu, R.
Source Titel Zenodo
Year 2022
Department ENVINF
Language englisch
Topic T8 Georesources
Abstract In the context of nuclear waste disposal, a pre-requisite to assure their long term safety is the need for safety assessment studies aided by computational simulations, in particular, radionuclide migration from the waste to the geosphere. It is established that underground repositories for nuclear waste will provide retardation barriers for radionuclides. However, the understanding of the sorption mechanisms of radionuclides onto mineral surfaces (i.e., illite, montmorillonite) is essential for modelling their migration. On the other hand, mechanistic-based radionuclide migration simulations, typically for 1 million years, poses a computational challenge. Surrogate-based simulations can be useful to enable sensitivity/uncertainty analysis that would be prohibitive otherwise. Considering the current challenges in modelling radionuclide migration and the importance of the results and implications of these simulations (i.e., for the public and nuclear waste management agencies) it is necessary to provide appropriate computational tools in a transparent and easy-to-use way. In this work, we aim to provide such tools in a framework that combines the simulation capabilities of OpenGeoSys6 for radionuclide migration and the approachable nature of Project Jupyter (i.e., JupyterLab), which provides a modular web-based environment for development, simulation and data. In this way, we aim to promote the collaborative research of radionuclide migration assessment and, at the same time, to guarantee the availability and reproducibility of the scientific outcome through the OpenGeoSys initiative.
Persistent UFZ Identifier
Garibay-Rodriguez, J., Chen, C., Shao, H., Bilke, L., Kolditz, O., Montoya, V., Lu, R. (2022):
Dataset for the paper: Computational framework for radionuclide migration assessment in clay rocks [Data set]
Zenodo 10.5281/zenodo.6614860